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Record W2800893791 · doi:10.7870/cjcmh-2017-031

The Implementation of the 2012 Mental Health Strategy for Canada Through the Lens of FASD

2017· article· en· W2800893791 on OpenAlexafffundvenueabout
Tara Anderson, Mansfield Mela, Michelle Stewart

Bibliographic record

VenueCanadian Journal of Community Mental Health · 2017
Typearticle
Languageen
FieldMedicine
TopicPrenatal Substance Exposure Effects
Canadian institutionsUniversity of SaskatchewanUniversity of Regina
FundersGovernment of NunavutGovernment of Alberta
KeywordsMental healthCommissionPerspective (graphical)PsychologyMedicinePsychiatryMedical educationApplied psychologyNursingPolitical scienceComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

It is the current authors’ perspective that the successful implementation of Changing Directions, Changing Lives, which seeks to improve mental health and well-being in Canada, cannot be realized effectively without considering FASD. Given that 94% of individuals with FASD also have mental disorders, practitioners in the mental health system are encountering these individuals every day. Most mental health professionals have not been trained to identify or diagnose FASD, and therefore it goes largely “unseen,” and individual treatment plans lack efficacy. Implementation of FASD-informed recommendations, such as those of the Truth and Reconciliation Commission of Canada (2015), can provide a more effective approach to mental health services and improve mental health outcomes.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.831
Threshold uncertainty score0.963

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0150.007
Scholarly communication0.0080.002
Open science0.0020.006
Research integrity0.0060.010
Insufficient payload (model declined to judge)0.0060.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.062
GPT teacher head0.378
Teacher spread0.316 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2017
Admission routes4
Has abstractyes

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